export all-in-focus

[RC1234]

I am trying to export from a .lfp file and create a .jpg, .tif, .png or similar image file that is all-in-focus.

I downloaded your scripts and tried the export feature and I don't understand, am I missing a script file named lfp_picture_exporter.py ? How do I get an all-in-focus image from your scripts?

Thanks in advance for any advice you can provide,

[bryantbeancox]

Hi,
The lfp-reader is teffitic and useful.But when the Lytro desktop update to 3.0,its lfp file can't be decompressed as usual.Do you know why?
Thanks all the same as the good thing have being provided.

[behnam]

@RC1234 In the latest version, lfp-picture.py export will give you all the frames, as well as the all-in-focus image.

Apparently the README file is out of date. I'm gonna fix it when I get some free time, or you can just send a pull request.

[behnam]

@bryantbeancox I don't have access to a Win/Mac machine to try out the latest Lytro Desktop app. I will look into it if you put a copy of the processed files from this version in the samples folder.

[behnam]

@bryantbeancox And please file another issues (pull request) for that matter.

[mioglez]

Hi Benham,

I too would like to know how to use/modify this package so that I can use files created by the new Lytro version. I have some processed files that I can share with you, but I'm not sure where this samples folder is to do so. In the meantime, I've pasted below the what the lfp-file.py shows about these new files. Thank you for all your hard work.

./lfp-file.py info file.lfp
Metadata:
{
    "picture": {
        "frameArray": [
            {
                "frame": {
                    "metadataRef": "sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01", 
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        "provisionalDate": "2012-10-23", 
        "minor": 0
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    "thumbnailArray": []
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and for the other -stk.lfp file

./lfp-file.py info file.lfp
Metadata:
{
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        "frameArray": [
            {
                "frame": {
                    "metadataRef": "sha1-6bab8cf2ebcc12e3e3cd29a6b89df8ef7ea1e787", 
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sha1-fb7618910f18aec65bf6d322cd2f0314fa77305f : 104218 B

[bryantbeancox]

Hello,
Actually I am not Benham the man you are looking for.I am just one of users of his lfp-reader.In the first time when the Lytro applicant upgraded,I encountered the same problem.But I found it still could work.
First,the folder keeping the file of lfp has changed.You must find it first.And then you can find the only useful(I think) file,the raw.You can also decompress the raw file as the same and get the same result.You just mail me the long data is the description of the Lytro data,including many details such as arrangement mode,focus length and so on.You have to check it out one by one if you want to do more things about this field.
At last,you'd better visit a toolbox named LFToolbox.You can download it on the Internet for free.It's a toolbox for matlab used with the lfp-reader at the same time,I think maybe it's good for your work.

with best wishes

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月24日(星期四) 上午10:44
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Hi Benham,

I too would like to know how to use lfp reader with the new version of Lytro Desktop. I have some lfp files that I would like to share with you and upload to the samples folder but I am not sure how to do that. In the mean time, here is the information the lfp reader spits for these lfp files.
./lfp-file.py info file.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [], "derivationArray": [ "sha1-96f6cdce552cc32904dcffb1849953da1705972a" ], "viewArray": [ { "vendorContent": { "starred": false }, "type": "com.lytro.stars" } ] }, "version": { "major": 1, "provisionalDate": "2012-10-23", "minor": 0 }, "thumbnailArray": [] } Data Chunks: 2 sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20 : 16137600 B sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01 : 3160 B
and for the -stk.lfp file
./lfp-file.py info file-stk.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-6bab8cf2ebcc12e3e3cd29a6b89df8ef7ea1e787", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20", "privateMetadataRef": "sha1-2dfc22987cc040f84ee6e435ce1770267884ec4c" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [ { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7435a07c5ba87c2844746c66cc61a460cf095538", "lambda": -10.398540496826172, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-e9763ddafbc52b466e87aa8e7520e559a88772ae", "lambda": -8.897197723388672, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-c8e0fc8f874274a2cd45e6bfe1b340912993fc85", "lambda": -7.887851715087891, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-24a247ff483670c19b59297f3ad24f4c25a7afab", "lambda": -6.361509799957275, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-48bc5a3bdca528ef68858c6e213b4ea9b8f75d33", "lambda": -4.859812259674072, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-fb7618910f18aec65bf6d322cd2f0314fa77305f", "lambda": -3.8504674434661865, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-07822916ab2df58de80a27db13753d90221829ac", "lambda": -2.419524669647217, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-487bbc226c74c1f494c51b09a270dd61c3552272", "lambda": -1.5104750394821167, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-235f788a62aa33272572ba1a2726e49ea902e875", "lambda": 1.200000286102295, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7b00fd8590396d8f7516cf481b4d2370a3b1f890", "lambda": 2.2056100368499756, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-5b1b7b28277851a71431276bebfa911a50a6098d", "lambda": 3.2149524688720703, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-22ed00a79d66b49dce087782be6f2e54c26d0c2b", "lambda": 4.224298477172852, "width": 1080 } ], "defaultLambda": 1.5, "displayParameters": { "displayDimensions": { "mode": "fixedToValue", "value": { "width": 1080, "height": 1080 } } }, "depthLut": { "width": 330, "representation": "raw", "imageRef": "sha1-37d14b82c8cbc9a7a27770793e48b05a017f7144", "height": 330 } }, "type": "com.lytro.acceleration.refocusStack", "generator": "Lytro Lightfield Engine 14.000000" }, { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-cc914c34f27a89d95982b8eb66feef63b50367aa", "coord": { "y": -0.2590940594673157, "x": 0.14958801865577698 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": 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[mioglez]

Thank you for answering my email. I'll certainly get to downloading the matlab file. I do have one question: what do you mean by the folder keeping the file of lfp has changed? I assume that the contents have indeed changed, such as there being only 2 data chunks instead of 3, the depth LUT possibly changing, and it not being encoded in h264. But what else do you mean?

El Apr 25, 2014, a las 1:30 AM, bryantbeancox notifications@github.com escribió:

Hello,
Actually I am not Benham the man you are looking for.I am just one of users of his lfp-reader.In the first time when the Lytro applicant upgraded,I encountered the same problem.But I found it still could work.
First,the folder keeping the file of lfp has changed.You must find it first.And then you can find the only useful(I think) file,the raw.You can also decompress the raw file as the same and get the same result.You just mail me the long data is the description of the Lytro data,including many details such as arrangement mode,focus length and so on.You have to check it out one by one if you want to do more things about this field.
At last,you'd better visit a toolbox named LFToolbox.You can download it on the Internet for free.It's a toolbox for matlab used with the lfp-reader at the same time,I think maybe it's good for your work.

with best wishes

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月24日(星期四) 上午10:44
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Hi Benham,

I too would like to know how to use lfp reader with the new version of Lytro Desktop. I have some lfp files that I would like to share with you and upload to the samples folder but I am not sure how to do that. In the mean time, here is the information the lfp reader spits for these lfp files.
./lfp-file.py info file.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [], "derivationArray": [ "sha1-96f6cdce552cc32904dcffb1849953da1705972a" ], "viewArray": [ { "vendorContent": { "starred": false }, "type": "com.lytro.stars" } ] }, "version": { "major": 1, "provisionalDate": "2012-10-23", "minor": 0 }, "thumbnailArray": [] } Data Chunks: 2 sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20 : 16137600 B sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01 : 3160 B
and for the -stk.lfp file
./lfp-file.py info file-stk.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-6bab8cf2ebcc12e3e3cd29a6b89df8ef7ea1e787", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20", "privateMetadataRef": "sha1-2dfc22987cc040f84ee6e435ce1770267884ec4c" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [ { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7435a07c5ba87c2844746c66cc61a460cf095538", "lambda": -10.398540496826172, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-e9763ddafbc52b466e87aa8e7520e559a88772ae", "lambda": -8.897197723388672, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-c8e0fc8f874274a2cd45e6bfe1b340912993fc85", "lambda": -7.887851715087891, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-24a247ff483670c19b59297f3ad24f4c25a7afab", "lambda": -6.361509799957275, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-48bc5a3bdca528ef68858c6e213b4ea9b8f75d33", "lambda": -4.859812259674072, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-fb7618910f18aec65bf6d322cd2f0314fa77305f", "lambda": -3.8504674434661865, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-07822916ab2df58de80a27db13753d90221829ac", "lambda": -2.419524669647217, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-487bbc226c74c1f494c51b09a270dd61c3552272", "lambda": -1.5104750394821167, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-235f788a62aa33272572ba1a2726e49ea902e875", "lambda": 1.200000286102295, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7b00fd8590396d8f7516cf481b4d2370a3b1f890", "lambda": 2.2056100368499756, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-5b1b7b28277851a71431276bebfa911a50a6098d", "lambda": 3.2149524688720703, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-22ed00a79d66b49dce087782be6f2e54c26d0c2b", "lambda": 4.224298477172852, "width": 1080 } ], "defaultLambda": 1.5, "displayParameters": { "displayDimensions": { "mode": "fixedToValue", "value": { "width": 1080, "height": 1080 } } }, "depthLut": { "width": 330, "representation": "raw", "imageRef": "sha1-37d14b82c8cbc9a7a27770793e48b05a017f7144", "height": 330 } }, "type": "com.lytro.acceleration.refocusStack", "generator": "Lytro Lightfield Engine 14.000000" }, { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-cc914c34f27a89d95982b8eb66feef63b50367aa", "coord": { "y": -0.2590940594673157, "x": 0.14958801865577698 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-07b66fec91bc5c887c7f4fec905209eaa541515e", "coord": { "y": -0.2590940594673157, "x": 0.04986267536878586 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-5e51177346f1d6e01acabb0ad13ab8c891ce4209", "coord": { "y": -0.2590940594673157, "x": -0.04986267536878586 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-96baa724bfc69f293d196be094d84cdd1591fab4", "coord": { "y": -0.2590940594673157, "x": -0.14958801865577698 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7f229de0ea9ba17e0761a6820d655a3093d3aeae", "coord": { "y": -0.17272937297821045, "x": -0.19945070147514343 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-c66f8e22a0037c136d3e956d2fd05e4e1f9c2ff8", "coord": { "y": -0.17272937297821045, "x": -0.09972535073757172 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-acf4e23120b296d7dd0b1d3a8a7f560b1581354b", "coord": { 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[bryantbeancox]

Yeah.It indeed has some changes.But you can still get the the file of raw and jason with the command of "lfp-picture.py export sample/IMG_0001.LFP",and then the matlab toolbox can do the rest.Actually I am not very care about its store format.So that's all what I get.

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月25日(星期五) 晚上9:34
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Thank you for answering my email. I'll certainly get to downloading the matlab file. I do have one question: what do you mean by the folder keeping the file of lfp has changed? I assume that the contents have indeed changed, such as there being only 2 data chunks instead of 3, the depth LUT possibly changing, and it not being encoded in h264. But what else do you mean?

El Apr 25, 2014, a las 1:30 AM, bryantbeancox notifications@github.com escribió:

Hello,
Actually I am not Benham the man you are looking for.I am just one of users of his lfp-reader.In the first time when the Lytro applicant upgraded,I encountered the same problem.But I found it still could work.
First,the folder keeping the file of lfp has changed.You must find it first.And then you can find the only useful(I think) file,the raw.You can also decompress the raw file as the same and get the same result.You just mail me the long data is the description of the Lytro data,including many details such as arrangement mode,focus length and so on.You have to check it out one by one if you want to do more things about this field.
At last,you'd better visit a toolbox named LFToolbox.You can download it on the Internet for free.It's a toolbox for matlab used with the lfp-reader at the same time,I think maybe it's good for your work.

with best wishes

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月24日(星期四) 上午10:44
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Hi Benham,

I too would like to know how to use lfp reader with the new version of Lytro Desktop. I have some lfp files that I would like to share with you and upload to the samples folder but I am not sure how to do that. In the mean time, here is the information the lfp reader spits for these lfp files.
./lfp-file.py info file.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [], "derivationArray": [ "sha1-96f6cdce552cc32904dcffb1849953da1705972a" ], "viewArray": [ { "vendorContent": { "starred": false }, "type": "com.lytro.stars" } ] }, "version": { "major": 1, "provisionalDate": "2012-10-23", "minor": 0 }, "thumbnailArray": [] } Data Chunks: 2 sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20 : 16137600 B sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01 : 3160 B
and for the -stk.lfp file
./lfp-file.py info file-stk.lfp Metadata: { "picture": { "frameArray": [ { "frame": { "metadataRef": "sha1-6bab8cf2ebcc12e3e3cd29a6b89df8ef7ea1e787", "imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20", "privateMetadataRef": "sha1-2dfc22987cc040f84ee6e435ce1770267884ec4c" }, "parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false, "modulationFrame": false } } } } ], "accelerationArray": [ { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7435a07c5ba87c2844746c66cc61a460cf095538", "lambda": -10.398540496826172, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-e9763ddafbc52b466e87aa8e7520e559a88772ae", "lambda": -8.897197723388672, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-c8e0fc8f874274a2cd45e6bfe1b340912993fc85", "lambda": -7.887851715087891, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-24a247ff483670c19b59297f3ad24f4c25a7afab", "lambda": -6.361509799957275, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-48bc5a3bdca528ef68858c6e213b4ea9b8f75d33", "lambda": -4.859812259674072, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-fb7618910f18aec65bf6d322cd2f0314fa77305f", "lambda": -3.8504674434661865, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-07822916ab2df58de80a27db13753d90221829ac", "lambda": -2.419524669647217, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-487bbc226c74c1f494c51b09a270dd61c3552272", "lambda": -1.5104750394821167, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-235f788a62aa33272572ba1a2726e49ea902e875", "lambda": 1.200000286102295, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-7b00fd8590396d8f7516cf481b4d2370a3b1f890", "lambda": 2.2056100368499756, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-5b1b7b28277851a71431276bebfa911a50a6098d", "lambda": 3.2149524688720703, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": "sha1-22ed00a79d66b49dce087782be6f2e54c26d0c2b", "lambda": 4.224298477172852, "width": 1080 } ], "defaultLambda": 1.5, "displayParameters": { "displayDimensions": { "mode": "fixedToValue", "value": { "width": 1080, "height": 1080 } } }, "depthLut": { "width": 330, "representation": "raw", "imageRef": "sha1-37d14b82c8cbc9a7a27770793e48b05a017f7144", "height": 330 } }, "type": "com.lytro.acceleration.refocusStack", "generator": "Lytro Lightfield Engine 14.000000" }, { "vendorContent": { "imageArray": [ { "representation": "jpeg", "height": 1080, "imageRef": "sha1-cc914c34f27a89d95982b8eb66feef63b50367aa", "coord": { "y": -0.2590940594673157, "x": 0.14958801865577698 }, "width": 1080 }, { "representation": "jpeg", "height": 1080, "imageRef": 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[mioglez]

Well I think the problem is that since the file is different, the
lfp-picture.py export/info commands don't work for these version 3 files;
instead, it gives the error "Not a valid/supported LFP Picture file. This
is why I wanted to know if there was anything I could do to update the code
so that it could support them. The only way that I have been able to work
with them is straight from the lfpsplitter command from nrpatel's lfptools.
I will see if this matlab program can do anything about it.

On Fri, Apr 25, 2014 at 10:19 AM, bryantbeancox notifications@github.comwrote:

Yeah.It indeed has some changes.But you can still get the the file of raw
and jason with the command of "lfp-picture.py export
sample/IMG_0001.LFP",and then the matlab toolbox can do the rest.Actually I
am not very care about its store format.So that's all what I get.

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月25日(星期五) 晚上9:34
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Thank you for answering my email. I'll certainly get to downloading the
matlab file. I do have one question: what do you mean by the folder keeping
the file of lfp has changed? I assume that the contents have indeed
changed, such as there being only 2 data chunks instead of 3, the depth LUT
possibly changing, and it not being encoded in h264. But what else do you
mean?

El Apr 25, 2014, a las 1:30 AM, bryantbeancox notifications@github.com
escribió:

Hello,
Actually I am not Benham the man you are looking for.I am just one of
users of his lfp-reader.In the first time when the Lytro applicant
upgraded,I encountered the same problem.But I found it still could work.
First,the folder keeping the file of lfp has changed.You must find it
first.And then you can find the only useful(I think) file,the raw.You can
also decompress the raw file as the same and get the same result.You just
mail me the long data is the description of the Lytro data,including many
details such as arrangement mode,focus length and so on.You have to check
it out one by one if you want to do more things about this field.
At last,you'd better visit a toolbox named LFToolbox.You can download it
on the Internet for free.It's a toolbox for matlab used with the lfp-reader
at the same time,I think maybe it's good for your work.

with best wishes

------------------ 原始邮件 ------------------
发件人: "mioglez";notifications@github.com;
发送时间: 2014年4月24日(星期四) 上午10:44
收件人: "behnam/python-lfp-reader"python-lfp-reader@noreply.github.com;
抄送: "kobe"541340151@qq.com;
主题: Re: [python-lfp-reader] export all-in-focus (#1)

Hi Benham,

I too would like to know how to use lfp reader with the new version of
Lytro Desktop. I have some lfp files that I would like to share with you
and upload to the samples folder but I am not sure how to do that. In the
mean time, here is the information the lfp reader spits for these lfp
files.
./lfp-file.py info file.lfp Metadata: { "picture": { "frameArray": [ {
"frame": { "metadataRef": "sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01",
"imageRef": "sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20" },
"parameters": { "vendorContent": { "com.lytro.tags": { "darkFrame": false,
"modulationFrame": false } } } } ], "accelerationArray": [],
"derivationArray": [ "sha1-96f6cdce552cc32904dcffb1849953da1705972a" ],
"viewArray": [ { "vendorContent": { "starred": false }, "type":
"com.lytro.stars" } ] }, "version": { "major": 1, "provisionalDate":
"2012-10-23", "minor": 0 }, "thumbnailArray": [] } Data Chunks: 2
sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20 : 16137600 B
sha1-2a485bbb2fcdc533e7fbb55a0a04ae438fc9cb01 : 3160 B
and for the -stk.lfp file
./lfp-file.py info file-stk.lfp Metadata: { "picture": { "frameArray": [
{ "frame": { "metadataRef":
"sha1-6bab8cf2ebcc12e3e3cd29a6b89df8ef7ea1e787", "imageRef":
"sha1-10495ef6b1de66c4d1459a512f2aca697fae3b20", "privateMetadataRef":
"sha1-2dfc22987cc040f84ee6e435ce1770267884ec4c" }, "parameters": {
"vendorContent": { "com.lytro.tags": { "darkFrame": false,
"modulationFrame": false } } } } ], "accelerationArray": [ {
"vendorContent": { "imageArray": [ { "representation": "jpeg", "height":
1080, "imageRef": "sha1-7435a07c5ba87c2844746c66cc61a460cf095538",
"lambda": -10.398540496826172, "width": 1080 }, { "representation": "jpeg",
"height": 1080, "imageRef":
"sha1-e9763ddafbc52b466e87aa8e7520e559a88772ae", "lambda":
-8.897197723388672, "width": 1080 }, { "representation": "jpeg", "height":
1080, "imageRef": "sha1-c8e0fc8f874274a2cd45e6bfe1b340912993fc85",
"lambda": -7.887851715087891, "width": 1080 }, { "representation": "jpeg",
"height": 1080, "imageRef":
"sha1-24a247ff483670c19b59297f3ad24f4c25a7afab", "lambda":
-6.361509799957275, "width": 1080 }, { "representation": "jpeg", "height":
1080, "imageRef": "sha1-48bc5a3bdca528ef68858c6e213b4ea9b8f75d33",
"lambda": -4.859812259674072, "width": 1080 }, { "representation": "jpeg",
"height": 1080, "imageRef":
"sha1-fb7618910f18aec65bf6d322cd2f0314fa77305f", "lambda":
-3.8504674434661865, "width": 1080 }, { "representation": "jpeg", "height":
1080, "imageRef": "sha1-07822916ab2df58de80a27db13753d90221829ac",
"lambda": -2.419524669647217, "width": 1080 }, { "representation": "jpeg",
"height": 1080, "imageRef":
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[behnam]

Hi there,

I haven't got the time to update this library to support the latest changes in the file format, but from the metadata dump you posted, looks like there hasn't been a huge change—at least in how focused JPEG files are saved—and should be easy to get it work.

I'll take a look myself when I get some time, but in the meanwhile, it would be great if someone can send a push-request to add the latest versions of the sample files to the repo. If you like to do so, please use the files existing under samples, add them to your library, and have desktop app update the file format.

-b